This study used perilla seeds produced in 2019, 2020, and 2021 to determine the year of production using multivariate statistical analysis of Fourier-transform infrared (FTIR) spectral data of perilla leaves. Spectral analysis based on multivariate statistical analysis of whole-cell extracts was used to distinguish the perilla leaves at the metabolic level. FT-IR spectral data of the leaves were analyzed using principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA). The FTIR spectrum identified spectral differences between the frequency regions of 1,700 to 1,500, 1,500 to 1,300, and 1,100 to 950 cm-1. This spectral region reflects quantitative and qualitative changes in amides I, II in amino acids and proteins (1,700–1,500 cm-1), phosphodiester groups from nucleic acids and phospholipids (1,500–1,300 cm-1), and carbohydrate compounds (1,100–950 cm-1). PCA revealed separate clusters corresponding to production traceability relationships. Therefore, PCA can be used to distinguish between production in 2019, 2020, and 2021 based on different metabolite contents. PLS-DA showed a similar production traceability classification for the perilla seeds. In addition, this metabolic identification system can be used to rapidly select and classify useful perilla seed varieties.
FT-IR spectroscopy, combined with multivariate analysis, was used to determine whether 67 different wild and rootstock peach accessions could be discriminated from each other. Genomic DNA was isolated from leaves, and the purified genomic DNA was analyzed by FT-IR spectroscopy in the spectral region from 1800 to 800 cm-1. FT-IR spectra showed that typical spectral differences existed in the frequency regions of N-H stretching (amide I), C=O stretching vibrations (amide II), and PO2− ionized asymmetric and symmetric stretching. Principal component analysis (PCA) was able to discriminate three groups. The partial least squares discriminant analysis (PLS-DA) yielded more clear discrimination among the three groups of peach accessions. The FT-IR spectral differences might be directly related to subtle changes in the base functional group and backbone structures of genomic DNA. This technique could provide a research foundation for FT-IR spectral-based rapid diagnosis, selection, and discrimination of peach accessions for rootstock.